887 research outputs found
Online Prediction of Dyadic Data with Heterogeneous Matrix Factorization
Dyadic Data Prediction (DDP) is an important problem in many research areas.
This paper develops a novel fully Bayesian nonparametric framework which
integrates two popular and complementary approaches, discrete mixed membership
modeling and continuous latent factor modeling into a unified Heterogeneous
Matrix Factorization~(HeMF) model, which can predict the unobserved dyadics
accurately. The HeMF can determine the number of communities automatically and
exploit the latent linear structure for each bicluster efficiently. We propose
a Variational Bayesian method to estimate the parameters and missing data. We
further develop a novel online learning approach for Variational inference and
use it for the online learning of HeMF, which can efficiently cope with the
important large-scale DDP problem. We evaluate the performance of our method on
the EachMoive, MovieLens and Netflix Prize collaborative filtering datasets.
The experiment shows that, our model outperforms state-of-the-art methods on
all benchmarks. Compared with Stochastic Gradient Method (SGD), our online
learning approach achieves significant improvement on the estimation accuracy
and robustness.Comment: 26 pages, 10 figure
Absolute cross-section normalization of magnetic neutron scattering data
We discuss various methods to obtain the resolution volume for neutron
scattering experiments, in order to perform absolute normalization on inelastic
magnetic neutron scattering data. Examples from previous experiments are given.
We also try to provide clear definitions of a number of physical quantities
which are commonly used to describe neutron magnetic scattering results,
including the dynamic spin correlation function and the imaginary part of the
dynamic susceptibility. Formulas that can be used for general purposes are
provided and the advantages of the different normalization processes are
discussed
Dynamics and Structure of PMN and PZN
A review is given of recent neutron and x-ray scattering studies of the
lead-oxide perovskite relaxor systems Pb(Zn1/3Nb2/3)O3-xPbTiO3 and
Pb(Mg1/3Nb2/3)O3-xPbTiO3. X-ray measurements by Noheda et al. have established
that these two systems exhibit nearly identical phase diagrams in which a
rhombohedral-monoclinic-tetragonal structural sequence takes place with
increasing PbTiO3 concentration. Recent high-energy x-ray and neutron
measurements on single crystals of PZN and PMN-10PT, however, show that the
rhombohedral distortions occur only in the outermost 20 - 40 microns, while the
bulk of each crystal transforms into a new phase X, which has a nearly cubic
unit cell. This situation is very similar to the structural behavior of pure
PMN at Tc = 220 K. A simple model has been suggested that correlates phase X to
the unique atomic displacements of the polar nanoregions, which are created at
the Burns temperature.Comment: conference proceeding for the NATO workshop on Disordered
Ferroelectrics. To be published on Ferroelectric
3-D mapping of diffuse scattering in PZN-xPT
High energy (67 keV) x-ray diffuse scattering measurements were performed on
single crystals of Pb(ZnNb)O-PbTiO (PZN-PT). A
novel technique was developed to map out the diffuse scattering distribution in
all three dimensions around a large number of Bragg peaks simultaneously,
taking advantage of the almost flat Ewald sphere of the high energy x-ray beam.
For , and 8%, the results are very similar, indicating same type of
correlations of polarizations in these compounds. Our results show that the
diffuse scattering intensity consists of six directions. A simple model is suggested where these soft phonon
modes condense into static \{110\} type planar or ``pancake'' shaped
correlations of the in-plane polarizations.Comment: Resolution/color of many figures are greatly reduced. For a higher
resolution version, go to
http://neutrons.phy.bnl.gov/~neutron/PZN_diffuse_3.pd
The Anomalous Skin Effect in Single Crystal Relaxor Ferroelectric PZN-xPT and PMN-xPT
X-ray and neutron scattering studies of the lead-based family of perovskite
relaxors PZN-PT and PMN-PT have documented a highly unusual situation in
which the near-surface region of a single crystal can exhibit a structure that
is different from that of the bulk when cooled to low temperatures. The
near-surface region, or "skin" can also display critical behavior that is
absent in the crystal interior, as well as a significantly different lattice
spacing. By varying the incident photon energy, and thus the effective
penetration depth, x-ray measurements indicate a skin thickness of order 10
m to 50 m for PZN-PT samples with %. Neutron
residual stress measurements on a large PMN single crystal reveal a uniform
lattice spacing within the bulk, but an increased strain near the surface. The
presence of this skin effect has led to incorrect phase diagrams for both the
PZN-PT and PMN-PT systems and erroneous characterizations of the nature
of the relaxor state.Comment: Review Articl
Phase instability induced by polar nanoregions in a relaxor ferroelectric system
Local inhomogeneities known as polar nanoregions (PNR) play a key role in
governing the dielectric properties of relaxor ferroelectrics - a special class
of material that exhibits an enormous electromechanical response and is easily
polarized with an external field. Using neutron inelastic scattering methods,
we show that the PNR can also significantly affect the structural properties of
the relaxor ferroelectric Pb(Zn1/3Nb2/3)O3-4.5%PbTiO3 (PZN-4.5%PT). A strong
interaction is found between the PNR and the propagation of sound waves, i.e.
acoustic phonons, the visibility of which can be enhanced with an external
electric field. A comparison between acoustic phonons propagating along
different directions reveals a large asymmetry in the lattice dynamics that is
induced by the PNR. We suggest that a phase instability induced by this
PNR-phonon interaction may contribute to the ultrahigh piezoelectric response
of this and related relaxor ferroelectric materials. Our results also naturally
explain the emergence of the various observed monoclinic phases in these
systems
Single-photon frequency conversion and multi-mode entanglement via constructive interference on Sagnac Loop
Based on constructive interference in Sagnac waveguide loop, an efficient
scheme is proposed for selective frequency conversion and multifrequency modes
W entanglement via input-output formalism. We can adjust the probability
amplitudes of output photons by choosing parameter values properly. The tunable
probability amplitude will lead to the generation of output photon with a
selectable frequency and W photonic entanglement of different frequencies modes
in a wide range of parameter values. Our calculations show the present scheme
is robust to the deviation of parameters and spontaneous decay
Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels
Noisy labels are ubiquitous in real-world datasets, which poses a challenge
for robustly training deep neural networks (DNNs) as DNNs usually have the high
capacity to memorize the noisy labels. In this paper, we find that the test
accuracy can be quantitatively characterized in terms of the noise ratio in
datasets. In particular, the test accuracy is a quadratic function of the noise
ratio in the case of symmetric noise, which explains the experimental findings
previously published. Based on our analysis, we apply cross-validation to
randomly split noisy datasets, which identifies most samples that have correct
labels. Then we adopt the Co-teaching strategy which takes full advantage of
the identified samples to train DNNs robustly against noisy labels. Compared
with extensive state-of-the-art methods, our strategy consistently improves the
generalization performance of DNNs under both synthetic and real-world training
noise.Comment: Correspondence to: Guangyong Chen <[email protected]
Superconductivity, Antiferromagnetism, and Neutron Scattering
High-temperature superconductivity in both the copper-oxide and the
iron-pnictide/chalcogenide systems occurs in close proximity to
antiferromagnetically ordered states. Neutron scattering has been an essential
technique for characterizing the spin correlations in the antiferromagnetic
phases and for demonstrating how the spin fluctuations persist in the
superconductors. While the nature of the spin correlations in the
superconductors remains controversial, the neutron scattering measurements of
magnetic excitations over broad ranges of energy and momentum transfer provide
important constraints on the theoretical options. We present an overview of the
neutron scattering work on high-temperature superconductors and discuss some of
the outstanding issues.Comment: 18 pages, to appear as a Current Perspective in J. Magn. Magn. Mate
Blind Image Denoising via Dependent Dirichlet Process Tree
Most existing image denoising approaches assumed the noise to be homogeneous
white Gaussian distributed with known intensity. However, in real noisy images,
the noise models are usually unknown beforehand and can be much more complex.
This paper addresses this problem and proposes a novel blind image denoising
algorithm to recover the clean image from noisy one with the unknown noise
model. To model the empirical noise of an image, our method introduces the
mixture of Gaussian distribution, which is flexible enough to approximate
different continuous distributions. The problem of blind image denoising is
reformulated as a learning problem. The procedure is to first build a two-layer
structural model for noisy patches and consider the clean ones as latent
variable. To control the complexity of the noisy patch model, this work
proposes a novel Bayesian nonparametric prior called "Dependent Dirichlet
Process Tree" to build the model. Then, this study derives a variational
inference algorithm to estimate model parameters and recover clean patches. We
apply our method on synthesis and real noisy images with different noise
models. Comparing with previous approaches, ours achieves better performance.
The experimental results indicate the efficiency of the proposed algorithm to
cope with practical image denoising tasks.Comment: 25 pages, 11 figure
- …